As an analytics professional or data scientist, you’re likely already adept at quantitative analysis and deriving insights from data. But, over the past few years, we’ve noticed more employers are really looking to hire professionals who can “bridge the gap” between technical chops (building models, data wrangling, etc.) and more strategic thinking.
Because of this, presentations have become much more common in the hiring process (learn more about how to ace interview presentations here). We’ve also gotten a lot of questions from analytics professionals and data scientists, asking about the best ways to demonstrate this critical thinking ability.
From our experience working with hiring managers, here are a few of our tips on ways that you can demonstrate strategic thinking:
1. Make your analysis actionable
What do the results of your analysis mean for the company? What should your team do next? How will this impact trends moving forward? These are all good questions to ask try and answer. Use the insights you’ve gathered from the data and think about what the next steps should be. Descriptive results can be helpful (we had X sales on Tuesday) but providing actionable insights (customers made X purchases on Tuesday because of Y, so we should do Z) demonstrate your ability to think strategically. Offer a course of action, either for further analysis or for the business.
2. Know the technical depth of your audience
Are you presenting to a technical manager? Or to the C-Suite, who might want more “big picture” details? Is there a timeframe that you’re working in that can give you a hint about how much detail to include? Your manager might want to know the statistical complexities and theories behind your results, but others might just want to top-line insights.
3. Know your audience’s priorities
Is this analysis for the marketing team or the finance team? What will this person find important or valuable? Different teams might have different priorities, and providing strategic insight often means coupling your quantitative expertise with context about what different teams find important or most helpful.
If you’re giving a presentation, even if it is a relatively casual setting, make sure you’re clear on the expected length, amount of detail, and scope that you’re expected to cover. Paying attention to the details and adjusting your presentation or report accordingly lets you deliver exactly what others need.
5. Provide examples that your audience can understand or relate to
Depending on who you’re delivering your analysis to, it might be helpful to think about related examples that your audience can relate your findings to, rather than delving into technical methodology.
6. Keep the bigger picture in mind
Similar to keeping analysis actionable, thinking about the bigger picture is about thinking beyond a single analysis, week, or month of data. Are there industry-wide factors you should be thinking about? Do you have contextual knowledge about outside factors that could be affecting your results, or could put your analysis in perspective?
7. Be proactive about improvement
We’ve written about this before, but asking for feedback and making adjustments to your approach is an excellent way to learn. Not only does this help you improve, but it’s good to know if you’re on the right track and delivering what everyone expects of you! Ask your manager how you can improve, ask for feedback on presentations or analysis, and don’t assume that your approach is the best one just because no one tells you otherwise.
As applications of analytics and data science continues to increase throughout the business world, we’ll continue to keep our eye on how this affects the hiring market. If you’re job searching or thinking about long-term career management, our colleague recently put out a great blog about how analytics and data science professionals can navigate today’s market. Best of luck!